Pulsed Ultrasonic Waves Research Articles

Adaptive Filtering of Pulse Waves for the Improvement of Ultrasonic Carotid LPWV Estimation Method

Abstract Aiming at promoting the accuracy of the ultrasonic carotid local pulse wave velocity (LPWV) estimation, an adaptive filtering of pulse waves for the ultrasonic carotid transit time-based LPWV estimation is proposed. First, the upstroke of pulse wave (PWU) is decomposed into time-frequency domain adaptively by an empirical wavelet transform (EWT) method, and then the noises (include the quantization noise and reflected wave in pulse wave) are picked up with predetermined threshold by multiple EWT decompositions. The proposed adaptive filtering of pulse waves for the LPWV estimation is quantitatively evaluated by an ultrasound simulation model for three age groups. Results show that the mean error of EWT-based PWU filtering are just 3.49 %, and the PWV estimation error for the three age groups are 5.77 ± 2.45 %, 4.54 ± 3.46 % and 12.24 ± 5.36 %, respectively by the EWT-based PWU filtering, which is lower than that by SG filtering. The results could be expected to provide theoretical basis and technical support for the early quantitative evaluation of local carotid vascular elasticity in clinic.

AI-assisted ultrasonic wave analysis for automated classification of steel corrosion-induced concrete damage

Early detection of cracks in reinforced concrete caused by chloride intrusion is crucial for effective maintenance. This paper develops and compares AI-assisted models that use ultrasonic pulse waves to automatically assess early-stage concrete damage, particularly cracks caused by steel corrosion. Data were collected from 108 concrete cubes with various mixture designs, cover depths, and steel corrosion levels induced by the impressed current technique. The AI models, particularly convolutional neural networks (CNNs), outperformed traditional regression models, achieving up to 84% classification accuracy. The systematic and automated features of the AI-assisted algorithm enable reliable, consistent and rapid ultrasonic wave data analysis, which is especially beneficial for the condition assessment of large infrastructure systems. This advancement inspires further research into integrating automated IoT and robotics-assisted systems for comprehensive infrastructure monitoring.

Advanced fabrication of polymer waveguide interferometric sensor utilizing interconnected holey fibers

A universally applicable approach is proposed for the fabrication of fiber-optic polymer sensors. The hollow-core fibers (HCFs) with inner diameters of 30 µm, 50 µm, and 75 µm are spliced coaxially with dual-hole fiber (DHF) or photonic crystal fiber (PCF). Owing to the sized-matched air holes within HCF and DHF/PCF, an interconnected in-fiber microchannel is constructed, which facilitates rapid and complete filling of the HCF’s central hole with liquid glue. After the ultraviolet-induced polymerization, a polymer Fabry-Perot interferometer is achieved by cutting the HCF end with a desired cavity length. Besides, the interference visibility is significantly enhanced by adding a refractive-index-modulated polymer cap onto the cutting surface. Experimental results demonstrate the optimized interference spectra and the interconnection of the matched air-hole fibers. The polymer sensor exhibits a signal-to-noise ratio of 56.8 dB for detecting pulsed ultrasonic waves, which is more than twice that of a partially polymer-filled sensor. Due to the hermetically-sealed structure, the sensor probe presents constrained performance with a temperature sensitivity of 230.2 pm/°C and a humidity sensitivity of 93.7 pm/%RH, which can be further improved by releasing the polymer waveguide from fiber cladding. Based on interconnected holey fibers, the proposed approach has a uniform size-controlled polymer waveguide dimension with increased spectrum visibility, rendering it suitable for a diverse range of microstructure-matched optical fibers.

Chloride-induced concrete deterioration monitoring using advanced ultrasonic pulse wave analysis based on convolutional neural network

This research explores the potential of deep learning techniques, specifically the convolutional neural network (CNN) architecture, for classifying concrete crack levels based on an acceptable threshold of concrete cracking. The classification model utilizes ultrasonic pulse wave data collected from concrete cube specimens before and after undergoing an accelerated corrosion process. A total of 108 concrete specimens, representing three different mix designs, three corrosion levels, and four concrete cover thicknesses, were utilized in this study. The collected data was employed to train CNN models, specifically leveraging the GoogLeNet and SqueezeNet architectures. Various input sampling rates, input lengths, and hyperparameters were explored to determine the optimal training setup, yielding the best prediction performance. The results demonstrate that the optimized models achieve an 84% accuracy in distinguishing cracks below and above the acceptable threshold. Therefore, it can be concluded that the CNN method holds potential for in-situ sensors aimed at monitoring chloride-induced deterioration in concrete structures.

An experimental study of tensile stress and deformation in an anisotropic rock

Anisotropy is a very common condition in rock mass; it can be due to different factors and directly affects the failure mechanisms affecting the rock mass. For example, metamorphic rocks that are foliated, sedimentary rocks that are stratified or volcanic formations with alternating layers. Despite the existence of several studies related to anisotropy those specifically addressing the tensile strength of anisotropic rocks are quite limited. The present study is focused on the determination of the deformability, compressive and tensile strength of anisotropic rocks. It must be highlighted that the mechanical behavior of the anisotropic rock mass is dependent on the angle between the inclination of planes of weakness (e.g. foliation) and the direction of the load. Assuming a vertical load, the two extremes of tensile strength are 0°(horizontal) and 90° (vertical). A series of laboratory tests has been done in anisotropic sandstone (lithic arkose), from Burgos (Spain), including uniaxial compressive strength tests, direct tensile strength tests, and diametric compression (Brazilian tests). The tests were carried out with strain gauges that allowed estimating the elastic modulus. To determine the anisotropic direction, ultrasonic pulse wave velocity tests were also performed. The variation of strength and deformability as a function of anisotropy is analyzed, as well as the variation of elastic behavior in tensile and compressive.

Strength Investigation of Slag-Based Geopolymer Composites Incorporating Different Amounts of Colemanite Waste and Silica Fume Under Different Exposure Conditions

In this study, it is aimed to investigate the strength performance of slag-based geopolymer mortar with different percentages of silica fume and colemanite waste by mixing Na₂SiO₃ and NaOH as the alkaline activator for the geopolymerization reaction, and cured at room temperature were prepared, in terms of compressive strength, flexural strength, ultrasonic pulse velocity and freeze-thaw resistance parameters. Five different mixtures were prepared by using different amounts of silica fume and colemanite waste by using the same amount of ground granulated blast furnace slag, sand and 8M sodium hydroxide for these five mixtures. The mixture, including a paste proportion of 20% slag, 40% colemanite waste, and 40% silica fume, was used as a control mix. The maximum compressive strength (21.24 MPa, 38.32 MPa) flexural strength (5.86 MPa, 6.98), weight loss caused by freeze-thaw effect (0.56%) and ultrasonic pulse wave test (3082 m/s) results were noted as for 7th and 28th day, respectively. After -60 cycles [1 cycle consists of (-18 oC) for 90 minutes and (+4 oC) for 30 minutes], the maximum compressive and flexural strength was observed as (40.18 MPa and 4.92 MPa, respectively). The results indicated that the strength results were consistently increased as silica fume increased. The addition of a certain amount of silica fume gave promising results both in terms of the strength and durability aspects. Overall, according to this experimental study, the utilization of 30% colemanite waste and 50% silica fume can be recommended so as to balance both sustainability and engineering aspects.

Evaluation of thermal damages of concrete subjected to high temperatures using recurrent neural networks for ultrasonic pulse waves

This study aims to propose the use of deep learning methods to classify the thermal damage of concrete cylinder specimens based on ultrasonic pulse wave data. Data are collected from laboratory experiments using concrete specimens with three different water-to-binder ratios (0.54, 0.46, and 0.35). The specimens are subjected to different target temperatures (100 °C, 200 °C, 300 °C, 400 °C and 600 °C) and another set of cylinders are subjected to just the room temperature to represent the normal temperature condition (20 °C). Thermal damages are classified using deep learning classification models based on three recurrent neural networks (long short-term memory, gated recurrent unit, and bidirectional long short-term memory) of the ultrasonic pulse wave data. It is demonstrated that deep learning yields a high accuracy in classifying thermal damage of concrete with a value of 88.24% based on the combination of instantaneous frequency and spectral entropy of ultrasonic times series with a sampling frequency of 1 MHz, as an input of the gated recurrent unit. The performance of the deep learning classification model is superior to models based on two conventional ultrasonic parameters (ultrasonic pulse velocity and signal coherence).

Evaluation of Early Concrete Damage Caused by Chloride-Induced Steel Corrosion Using a Deep Learning Approach Based on RNN for Ultrasonic Pulse Waves.

The objective of this study is to explore the feasibility of using ultrasonic pulse wave measurements as an early detection method for corrosion-induced concrete damages. A series of experiments are conducted using concrete cube specimens, at a size of 200 mm, with a reinforcing steel bar (rebar) embedded in the center. The main variables include the water-to-cement ratio of the concrete (0.4, 0.5, and 0.6), the diameter of the rebar (10 mm, 13 mm, 19 mm, and 22 mm), and the corrosion level (ranging from 0% to 20% depending on rebar diameter). The impressed current technique is used to accelerate corrosion of rebars in concrete immersed in a 3% NaCl solution. Ultrasonic pulse waves are collected from the concrete specimens using a pair of 50 kHz P-wave transducers in the through-transmission configuration before and after the accelerated corrosion test. Deep learning techniques, specifically three recurrent neural network (RNN) models (long short-term memory, gated recurrent unit, and bidirectional long short-term memory), are utilized to develop a classification model for early detection of concrete damage due to rebar corrosion. The performance of the RNN models is compared to conventional ultrasonic testing parameters, namely ultrasonic pulse velocity and signal consistency. The results demonstrate that the RNN method outperforms the other two methods. Among the RNN methods, the bidirectional long short-term memory RNN model had the best performance, achieving an accuracy of 74% and a Cohen's kappa coefficient of 0.48. This study establishes the potentiality of utilizing deep learning of ultrasonic pulse waves with RNN models for early detection of concrete damage associated with steel corrosion.

Ultrasonic Traveling Waves for Near-Wall Positioning of Single Microbubbles in a Flowing Channel.

Although microbubbles are used primarily in the medical industry as ultrasonic contrast agents, they can also be manipulated by acoustic waves for targeted drug delivery, sonothrombolysis and sonoporation. Acoustic waves can also potentially remove microbubbles from tubing systems (e.g., in hemodialysis) to prevent the negative effects associated with circulating microbubbles. A deeper understanding of the interactions between the acoustic radiation force, the microbubble and the channel wall could greatly benefit these applications. In this study, single air-filled microbubbles were injected into a flowing (polydimethylsiloxane) channel and monitored by a high-speed camera while passing through a pulsed ultrasonic wave zone (0.5 MHz). This study compared various bubble sizes, flow rates and acoustic pressure amplitudes to better understand the three physical regimes observed: free bubble translation (away from the wall); on-wall translation; and bubble-wall attachment. Comparison with a theoretical model revealed that the acoustic radiation force needs to exceed the combined repulsive forces (shear lift, wall lubrication and repulsive Van der Waal forces) for the dead state of bubble-wall attachment. The bubble dynamics revealed through this investigation provide an opportunity for efficient positioning of microbubbles in a channel flow, for either in vivo manipulation or removal in biological applications.

Acoustically driven translation of a single bubble in pulsed traveling ultrasonic waves

The acoustic radiation force has been proven as an effective mechanism for displacing particles and bubbles, but it has been mainly applied in a standing wave mode in microfluidics. Alternatively, the use of pulsed traveling acoustic waves could enable new options, but its transient dynamic, which entails the additional complexities of pulse timing, reflections, and the type of waveform, has not yet been fully investigated. To better understand these transient effects, a transient numerical solution and an experimental testbed were developed to gain insights into the displacement of microbubbles when exposed to on- and off-periods of pulsed traveling waves. In this study, a practical sinusoid tone burst excitation at a driving frequency of 0.5 MHz is investigated. Our numerical and experimental results were found to be in good agreement, with only a 13% deviation in the acoustically driven velocity. With greater detail from the numerical solution at a sampling rate of 1 GHz, the fundamental mechanism for the bubble translation was revealed. It was found that the added mass force, gained through the on-period of the pulse, continued to drive the bubble throughout the off-period, enabling a large total displacement, even in the case of low duty-cycle (2%) pulsing. In addition, the results showed greater translational velocity is possible with a lower number of cycles for the same input acoustic energy (constant duty cycle and acoustic pressure amplitude). Overall, this study proposes a new, practical, and scalable approach for the acoustic manipulation of microbubbles for scientific, biomedical, and industrial applications.

接触剛性によるボルト締結モデルと透過超音波パルスを用いた定量評価

Evaluation of bolt tightening plays an important role to keep a performance of a mechanical structure. Lack of the fastening force induces slack and falling of the tightening bolt. Excessive fastening force induces a plastic deformation of screw thread and causes the decline of the fastening force. Therefore, guarantee of the bolt tightening is an important subject in order to secure the mechanical structure against unforeseen accidents. However, most of preceding studies are restricted within qualitative evaluation of the slackness. In the field of industrial manufacturing, quantitative evaluation of the bolt tightening is strongly required. In this paper, the authors propose a technique for quantitative evaluation of bolt tightening, and in this technique, the flank of the screw thread is assumed to contact through a contact stiffness. The transmissivity and reflectivity of an ultrasonic pulse wave through the flank are derived as a function of contact stiffness, and the contact stiffness is capable of being identified from experimentally acquired amplitude of ultrasonic pulse wave. The contact stiffness is quantitatively identified and the surface pressure on the screw thread is estimated by the identified contact stiffness through the results of the preceding study. The proposed technique treats an ultrasonic pulse perpendicularly transmits a fastening bolt, and is applied to an experimentally acquired ultrasonic pulse which enters a side surface of nut and transmits a bolt-nut fastening element. The identified contact stiffness is shown to be adequate for the given fastening force to the bolt-nut fastening element, and validity of the proposed technique is demonstrated.

Micro-viscoelastic Characterization of Compressed Oral Solid Dosage Forms with Ultrasonic Wave Dispersion Analysis.

Due to their constituent powders, the materials of advanced compressed oral solid dosage (OSD) forms are micro-composites and strongly visco-elastic at macro- and micro-length scales. The disintegration, drug release, and mechanical strength of OSD forms depend on its micro-texture (such as porosity) and micro-scale physical/mechanical properties. In the current work, an algorithmic ultrasonic characterization framework for extracting the micro-visco-elastic properties of OSD materials is presented, and its applicability is demonstrated with a model material. The proposed approach is based on the effect of visco-elasticity and granularity on the frequency-dependent attenuation of an ultrasonic wave pulse in a composite (granular) and viscous medium. In modeling the material, a two-parameter Zener model for visco-elasticity and a scattering attenuation mechanism based on Rayleigh scattering for long-wave approximation are employed. A novel linear technique for de-coupling the effects of micro-visco-elasticity and scattering on attenuation and dispersion is developed and demonstrated. The apparent Young's modulus, stress, and strain relaxation time constants of the medium at micro-scale are extracted and reported. Based on this modeling and analysis framework, a set of computational algorithms has been developed and demonstrated with experimental data, and its practical utility in pharmaceutical manufacturing and real-time release testing of tablets is discussed.

Evaluation of Heat-Induced Damage in Concrete Using Machine Learning of Ultrasonic Pulse Waves.

This study investigated the applicability of using ultrasonic wave signals in detecting early fire damage in concrete. This study analyzed the reliability of using the linear (wave velocity) and nonlinear (coherence) parameters from ultrasonic pulse measurements and the applicability of machine learning in assessing the thermal damage of concrete cylinders. While machine learning has been used in some damage detections for concrete, its feasibility has not been fully investigated in classifying thermal damage. Data was collected from laboratory experiments using concrete specimens with three different water-to-binder ratios (0.54, 0.46, and 0.35). The specimens were subjected to different target temperatures (100 °C, 200 °C, 300 °C, 400 °C, and 600 °C) and another set of cylinders was subjected to room temperature (20 °C) to represent the normal temperature condition. It was observed that P-wave velocities increased by 0.1% to 10.44% when the concretes were heated to 100 °C, and then decreased continuously until 600 °C by 48.46% to 65.80%. Conversely, coherence showed a significant decrease after exposure to 100 °C but had fluctuating values in the range of 0.110 to 0.223 thereafter. In terms of classifying the thermal damage of concrete, machine learning yielded an accuracy of 76.0% while the use of P-wave velocity and coherence yielded accuracies of 30.26% and 32.31%, respectively.

Marly Soft Rocks: Correlation of Physical and Mechanical Properties—Examples from Dalmatia (Croatia) and Budapest (Hungary)

Soft rocks in various forms of marly materials have an important role in the geological structure of Dalmatia (Croatia) and Budapest region (Hungary). These materials can cause serious problems in design and construction, due to their complex behavior under atmospheric conditions. For the purpose of better understanding soft rocks behavior and their properties, a database with approximately 600 samples collected throughout Dalmatia was made and collated along with 260 samples from the Budapest area. Based on the collected data, 30 regression analyses were performed among 14 material properties, and eight different types of linear and non-linear correlations with high coefficients of determination were selected, which connect the important mechanical properties (uniaxial compressive strength and Young’s modulus) with physical properties of marls (porosity, dry unit weight, and ultrasonic pulse wave velocity). Most of the determined relations show symmetry between the marls from the Dalmatian region and the Budapest region, and the relation between dry unit weight and uniaxial compressive strength asymmetry can be observed between the marls with different origins. Obtained correlations may be used in cases where little or no information on geotechnical parameters is available, or where results need to be verified due to the problems present in soft rock testing.

Development of Test Methods to Evaluate the Printability of Concrete Materials for Additive Manufacturing.

This study proposes test methods for assessing the printability of concrete materials for Additive Manufacturing. The printability of concrete is divided into three main aspects: flowability, setting time, and buildability. These properties are considered to monitor the critical quality of 3DCP and to ensure a successful print. Flowability is evaluated through a rheometer test, where the evolution of shear yield strength is monitored at a constant rate (rpm), similar to the printer setup. Flowability limits were set based on the user-defined maximum thickness of a printed layer and the onset of gaps/cracks during printing. Setting time is evaluated through an ultrasonic wave pulse velocity test (UPV), where the first inflection point of the evolution of the UPV graph corresponds to the setting time of the concrete specimen. The results from this continuous non-destructive test were found to correlate with the results from the discrete destructive ASTM C-191 test for measuring setting time with a maximum difference of 5% between both sets of values. Lastly, buildability was evaluated through the measurement of the early-age compressive strength of concrete, and a correlation with the UPV results obtained a predictive model that can be used in real-time to non-destructively assess the material buildability. This predictive model had a maximum percentage difference of 13% with the measured values. The outcome of this study is a set of tests to evaluate the properties of 3D printable concrete (3DP) material and provide a basis for a framework to benchmark and design materials for additive manufacturing.

ÇİMENTO YERİNE KISMİ AHŞAP TABAN KÜLÜ İÇEREN HARÇLARIN MEKANİK ÖZELLİKLERİ

Carbon dioxide (CO2) released into the atmosphere during the production of Portland cement (PC) is one of the important factors causing global warming. Therefore, studies are carried out on different materials to reduce PC consumption. The effect levels of the wood bottom ash (WBA) ratio and specimen age on the response variables (compressive strength, flexural strength, and ultrasonic pulse velocity) were investigated in this study. Mortar specimens were produced using PC, WBA, CEN standard sand, and distilled water. The produced specimens were cured in water until the test day. WBA ratios are 0%, 5%, 10%, 20%, 35% and 50% by weight of binder. As a result, it was determined that the optimum WBA ratio was 5%. In addition, R2 values of response variables were found to be high (ultrasonic pulsed wave velocity; 0.8925, flexural strength; 0.9356, compressive strength; 0.9404) by analysis of variance (ANOVA). This shows that the models have a high correlation. Moreover, the terms added to the models have a significant effect on the responses.

Early age reaction, rheological properties and pore solution chemistry of NaOH-activated slag mixtures

In this study, the rheology and early reaction process of sodium hydroxide-activated ground granulated blast furnace slag (GGBFS) were investigated. Test results showed a strong relationship between the Vicat initial setting time and ultrasonic pulse wave for NaOH activated slag mixtures identifying the characteristic points or inflection points in the ultrasonic curves and reaching a specific value in the ultrasonic velocity. The early reaction process of the sodium hydroxide-activated slag pastes determined by ultrasonic pulse wave and calorimeter consisted of three stages: dissolution, acceleration/condensation and deceleration stages. The yield stress and apparent viscosity of the pastes increased by the addition of NaOH, and the pastes started to show shear-thickening behavior when NaOH concentration reached 8 M. It was also revealed that Si, Al and Ca ion concentrations in the pore solution increased with an increase in NaOH concentration, and the pore solution of the pastes was dominated by Na and OH−. No significant influence of NaOH concentrations upon 4 M on the compressive strength of the mortar samples was observed.

COMPARISON OF THE MECHANICAL PROPERTIES, HEAT PERMEABİLİTY CHARACTERISTICS AND RESISTANCE AGAINST HIGH TEMPERATURE OF LIGHT MORTARS MADE WITH EPS AND WASTE POLYURETHANE

Bu çalışmada endüstriyel işlem sonrası açığa çıkan atık poliüretanın hafif harç imalatında kullanımı araştırılmıştır. Hali hazırda hafif harç üretiminde kullanılan EPS (Expanded polystyren foam) ve atık poliüretan kullanılarak hafif harç numuneler üretilmiştir. Üretilen numuneler eşdeğer birim ağırlıklarına göre karşılaştırılarak, atık poliüretanın hafif harç imalatında kullanımı araştırılmıştır. Çalışma kapsamında EPS ve atık poliüretan agrega ile hacimce %20, %40, %60, %80, %100 oranlarında yer değiştirilerek kullanılmış ve 40x40x160 mm’lik prizmatik harç numuneler üretilmiştir. Üretilen harç numunelerin birim ağırlık değerleri, ultrasonik atımlı dalga hızları, ısı iletkenlik katsayıları ile eğilme ve basınç dayanımları ölçülmüştür. Ayrıca hem EPS hem de atık poliüretan ile üretilmiş harç numuneler 300⁰C, 600⁰C, 900⁰C’de yüksek sıcaklığa tabi tutulmuş ve sonrasında numunelerin mekanik dayanımları ile içyapıları incelenmiştir. İçyapı incelemeleri hamur numuneler üzerinde FESEM görüntüleri ile gerçekleştirilmiştir. Elde edilen verilere göre hem orta mukavemetli hafif beton sınıfına giren harçlarda, hem de taşıyıcı hafif beton sınıfına giren harçlarda atık poliüretan ile imal edilen harçların EPS’li harçlara göre daha iyi performans gösterdiği sonucuna varılmıştır. Özellikle yüksek sıcaklık sonrası mekanik dayanımlar incelendiğinde atık poliüretanlı harç numunelerin, EPS’li numunelere oranla daha yüksek eğilme ve basınç dayanımları verdiği tespit edilmiştir.

Hydration re-initiation of borated CSA systems with a two-stage mixing process: An application in extrusion-based concrete 3D printing

Enhanced structural build-up and strength development are crucial for various construction processes, especially in extrusion-based concrete 3D printing. However, controlling the stiffening process could be quite challenging as there are conflicting requirements during the pumping and deposition phase. We present a study to enhance the structural build-up of a calcium sulfoaluminate (CSA) cement-based system using a two-stage mixing method. A borated CSA cement mixture having a long open time (> two hours) was intermixed near the nozzle/print head of the 3D printer with a mixture of limestone and calcium hydroxide having an indefinite open time. The hydration and the early-age mechanical behaviour of the different combinations of these two mixtures were investigated by isothermal calorimetry, XRD analysis, unconfined compression tests, and ultrasonic pulse wave velocity tests. The results indicate that in the presence of calcium hydroxide, the borated phase (ulexite) covering the ye'elimite and being responsible for the long open time, rapidly destabilizes and the hydration reaction re-initiates. The hydration progresses rapidly, resulting in enhanced pore segmentation and a rapid increase in mechanical properties (compressive strength and elastic modulus), significantly faster than what is reported for conventional 3D printable concrete. Finally, a 1.5 m tall column was printed with this two-stage mixing method in a time period of <10 min – demonstrating the feasibility of the developed mixture for 3D printing applications.

Evaluation of the crack-healing performance and durability of bacteria integrated alkali-activated fly ash composites

This study aims to introduce Bacillus Cohnii endospores into an alkali-activated fly ash-based composite (AAFC) to improve the crack-healing properties and durability while maintaining an environment-friendly strategy. Few important parameters such as water absorption capacity, sulfate resistivity, rapid chloride ions penetration, and its migration through bacteria impregnated AAFC (Bio-AAFC) are considered for the assessment of the healed structure's activities. The cracks up to 0.59 mm width dimension are completely plugged up and 12% of mechanical strength of healed-AAFC is regained within 28 days, determined in the microscopic study, strength gains calculation, and velocity of ultrasonic pulse waves assessment. Bio-mineral precipitation into Bio-AAFC produces durable concrete, particularly in chloride and sulfate-laden environments. Due to calcium/sodium carbonate precipitation in pores and voids, the microstructure of the biosystem became compact and dense, resulting in excellent performances. It is the microbial activity for the biomineralization process that causes mainly calcium carbonate deposition to reduce pore size (35% average 510 nm pore diameter) in Bio-AAFC samples, thereby verifying the bacterial endospores can persist for a long time inside AAFC. Specifically, Bio-AAFC, having magnificent durability and crack-healing abilities explores the recycling of industrial dry wastes in a promising way.